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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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a key point to lower manufacturing costs. For this purpose, silicon substrates are used as a support, but the large differences in crystalline properties (lattice parameters, expansion coefficients
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projects; this can entail working alongside domain experts to extract relevant knowledge, and programming using suitable models to infuse that knowledge with ML methods, thus aiming to optimize performance
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experiments, including occasional wet lab work Merging experimental results, simulations, and literature for optimal conditions inducing movement differences, in collaboration with the team. Participation in
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divided into four areas with respective subgroups: »Optimization« »Processes and Materials« »Mathematics for Vehicles, Systems, and Plants« »Analytics and Computing« What you contribute You have completed
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understanding of molecular thermodynamics, and realize the importance of different types of properties in selecting and developing the most physically sound thermodynamic model for water and electrolytes
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Job related to staff position within a Research Infrastructure? No Offer Description Would you like to contribute to reducing health inequalities by co-creating, evaluating, and optimizing an adapted
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(e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects of machine learning such as
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Engineering. Food approved microorganisms will be optimized using classical mutagenesis/screening and adaptive evolution. Genetic engineering will be used for guidance and to elucidate the effect of introduced
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different EU countries. All 15 PhD projects are within the overall theme of Silicon carbide on insulator (SiCOI) devices and integration for applications in classic and quantum optical telecommunication, and